Multi-level Monitoring and Analysis of Web-Scale Service Based Applications

Mos, Adrian; Pedrinaci, Carlos; Rey, Guillermo Álvaro; Gómez, José Manuel; Liu, Dong; Vaudaux-Ruth, Guillaume; Quaireau, Samuel

doi:10.1007/978-3-642-16132-2_26

Cited by 13 publications

(5 citation statements)

References 17 publications

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“…Consequently, the real problem is not correctly diagnosed, which may lead to the wrong identification of the source of problem. The works proposed in [17] [18] assume that the correlation of monitoring data from different resources and across different layers is a key requirement to ensure effective propagation of adaptation actions. However, correlation is always a limitation as events are inferred according to static correlation rules.…”

Section: Related Workmentioning

confidence: 99%

Towards trustworthy service adaptation: An ontology-based cross-layer approach

Mezni

2014

2014 IEEE 5th International Conference on Software Engineering and Service Science

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Although several approaches have been proposed towards self-adaptation of Web services, most of them work in isolation and few of them deal with cross-layer and trust issues. Indeed, the complex layered nature of service-based systems frequently leads to service failure and conflicting adaptation. To tackle this problem, we propose an ontology-based categorization of service behavior across all the functional layers. The proposed ontology provides support for cross-layer self-adaptation by facilitating reasoning about events to identify the real source of service failure, and reasoning about self-adaptation actions to check integrity and compatibility of self-adaptation with constraints imposed by each layer.

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Section: Related Workmentioning

confidence: 99%

Towards trustworthy service adaptation: An ontology-based cross-layer approach

Mezni

2014

2014 IEEE 5th International Conference on Software Engineering and Service Science

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“…Complementary work from the field of monitoring and analysis of web-scale service-based applications like [15] aims at understanding and analyzing serviceoriented applications and detecting and preventing potential misbehavior.…”

Section: Related Workmentioning

confidence: 99%

When History Matters - Assessing Reliability for the Reuse of Scientific Workflows

Gómez-Pérez

García-Cuesta

Garrido

et al. 2013

Advanced Information Systems Engineering

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Abstract. Scientific workflows play an important role in computational research as essential artifacts for communicating the methods used to produce research findings. We are witnessing a growing number of efforts that treat workflows as first-class artifacts for sharing and exchanging scientific knowledge, either as part of scholarly articles or as stand-alone objects. However, workflows are not born to be reliable, which can seriously damage their reusability and trustworthiness as knowledge exchange instruments. Scientific workflows are commonly subject to decay, which consequently undermines their reliability over their lifetime. The reliability of workflows can be notably improved by advocating scientists to preserve a minimal set of information that is essential to assist the interpretations of these workflows and hence improve their potential for reproducibility and reusability. In this paper we show how, by measuring and monitoring the completeness and stability of scientific workflows over time we are able to provide scientists with a measure of their reliability, supporting the reuse of trustworthy scientific knowledge.

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“…A violation reporter generates a web page with information about detected violations, as well as a form for selecting a recovery plan. The SOA4All framework [27] provides three different views that visualize the key performance indicators of monitored processes and services, the human or mechanized resources required for executing processes, and the business objects such as inquiries, orders or claims. These views are supplemented with basic descriptive statistics.…”

Section: Visualization In Other Monitoring Toolsmentioning

confidence: 99%